Direct and simultaneous spectrophotometric determination of Ni (II) and Co (II) using diethanoldithiocarbamate as complexing agent

A direct spectrophotometric method for simultaneous determination of Co(II) and Ni(II), with diethanoldithiocarbamate (DEDC) as complexing agent, is proposed using the maximum absorption at 360 and 638 nm (Co(II)/DEDC) and 390 nm (Ni/DEDC). Adjusting the best metal/ligand ratio, supporting eletrolite, pH, and time of analysis, linear analytical curves from 1.0 10-6-4.0 10-4 for Co(II) in the presence of Ni 1.0 10-6-1.0 10-4 mol L-1 were observed. No further treatment or calculation processes have been necessary. Recoveries in different mixing ratios were of 99%. Interference of Fe(III), Cu(II), Zn(II) and Cd(II), and anions as NO3-, Cl-, ClO4-, citrate and phosphate has been evaluated. The method was applied to natural waters spiked with the cations.

Flow-batch analyser for preparation of calibration standard mixtures in simultaneous multicomponent spectrometric analysis

The application of multivariate calibration techniques to multicomponent analysis by UV-VIS molecular absorption spectrometry is a powerful tool for simultaneous determination of several chemical species. However, when this methodology is accomplished manually, it is slow and laborious, consumes high amounts of reagents and samples, is susceptible to contaminations and presents a high operational cost. To overcome these drawbacks, a flow-batch analyser is proposed in this work. This analyser was developed for automatic preparation of standard calibration and test (or validation) mixtures. It was applied to the simultaneous determination of Cu2+, Mn2+ and Zn2+ in polyvitaminic and polymineral pharmaceutical formulations, using 4-(2-piridilazo) resorcinol as reagent and a UV-VIS spectrophotometer with a photodiode array detector. The results obtained with the proposed system are in good agreement with those obtained by flame atomic absorption spectrometry, which was employed as reference method. With the proposed analyser, the preparation of calibration and test mixtures can be accomplished about four hours, while the manual procedure requires at least two days. Moreover, it consumes smaller amounts of reagents and samples than the manual procedure. After the preparation of calibration and test mixtures, 60 samples h-1 can be carried out with the proposed flow-batch analyser.

Optimization of NMP extraction in 1, 3-butadiene production line

N-methylpyrrolidone is a powerful solvent for variety of chemical processes due to its vast chemical properties. It has been used in manufacturing processes of polymers, detergents, pharmaceuticals rubber and many more chemical substances. However, it creates large amount of residue in some of these processes which has to be dealt with. Many well known methods such as BASF in rubber producing units have tried to regenerate the solvent at the end of each run, however, there is still discarding of large amount of residue containing NMP, which over time, could cause environmental concerns. In this study, we have tried to optimize regeneration of the NMP extraction from butadiene production. It is shown that at higher temperatures NMP is separated from the residue with close to 90% efficiency, and the solvent residue proved to be the most effective with a 6: 1 ratio.

Development and validation of spectroscopic methods for simultaneous estimation and dissolution of ofloxacin and ornidazole in tablet dosage forms

The aim of this work was to develop and validate simple, accurate and precise spectroscopic methods (multicomponent, dual wavelength and simultaneous equations) for the simultaneous estimation and dissolution testing of ofloxacin and ornidazole tablet dosage forms. The medium of dissolution used was 900 ml of 0.01N HCl, using a paddle apparatus at a stirring rate of 50 rpm. The drug release was evaluated by developed and validated spectroscopic methods. Ofloxacin and ornidazole showed 293.4 and 319.6nm as λmax in 0.01N HCl. The methods were validated to meet requirements for a global regulatory filing. The validation included linearity, precision and accuracy. In addition, recovery studies and dissolution studies of three different tablets were compared and the results obtained show no significant difference among products.

Complexity Optimization in Product Development with Modularization

A company’s competence to manage its product portfolio complexity is becoming critically important in the rapidly changing business environment. The continuous evolvement of customer needs, the competitive market environment and internal product development lead to increasing complexity in product portfolios. The companies that manage the complexity in product development are more profitable in the long run. The complexity derives from product development and management processes where the new product variant development is not managed efficiently. Complexity is managed with modularization which is a method that divides the product structure into modules. In modularization, it is essential to take into account the trade-off between the perceived customer value and the module or component commonality across the products. Another goal is to enable the product configuration to be more flexible. The benefits are achieved through optimizing complexity in module offering and deriving the new product variants more flexibly and accurately. The developed modularization process includes the process steps for preparation, mapping the current situation, the creation of a modular strategy and implementing the strategy. Also the organization and support systems have to be adapted to follow-up targets and to execute modularization in practice.

Optimization of invertase assay conditions in rubber tree plants (Hevea brasiliensis Muell. Arg.)

The objective of this work was to define the optimal conditions for invertase assay, seeking to determine the ideal parameters for the different isoenzymes of leaf and bark tissues in adult rubber trees. Assays of varying pH, sucrose concentration and temperature of the reaction medium were conducted for the two investigated isoenzymes. The results pointed out the existence of two different pH related isoforms for the two analyzed tissues, with an isoenzyme being more active at pH 5,5 and the other at neutral/alkaline pH. Leaf blade isoenzymes presented similar values for substrate concentration, whereas the bark isoenzyme presented maximum values below those previously reported. The assays at different temperatures presented similar values for leaf isoenzymes, though they have differed significantly among the obtained values.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

MCMC Analysis for Optimization of Stochastic Models

In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

Optimization of the refining and shoe press in board production

Optimointi on tavallinen toimenpide esimerkiksi prosessin muuttamisen tai uusimisen jälkeen. Optimoinnilla pyritään etsimään vaikkapa tiettyjen laatuominaisuuksien kannalta paras tapa ajaa prosessia tai erinäisiä prosessin osia. Tämän työn tarkoituksena oli investoinnin jälkeen optimoida neljä muuttujaa, erään runkoon menevän massan jauhatus ja määrä, märkäpuristus sekä spray –tärkin määrä, kolmen laatuominaisuuden, palstautumislujuuden, geometrisen taivutusjäykkyyden ja sileyden, suhteen. Työtä varten tehtiin viisi tehdasmittakaavaista koeajoa. Ensimmäisessä koeajossa oli tarkoitus lisätä vettä tai spray –tärkkiä kolmikerroskartongin toiseen kerrosten rajapintaan, toisessa koeajossa muutettiin, jo aiemmin mainitun runkoon menevän massan jauhatusta ja jauhinkombinaatioita. Ensimmäisessä koeajossa tutkittiin palstautumislujuuden, toisessa koeajossa muiden lujuusominaisuuksien kehittymistä. Kolmannessa koeajossa tutkittiin erään runkoon menevän massan jauhatuksen ja määrän sekä kenkäpuristimen viivapaineen muutoksen vaikutusta palstautumislujuuteen, geometriseen taivutusjäykkyyteen sekä sileyteen. Neljännessä koeajossa yritettiin toistaa edellisen koeajon paras piste ja parametreja hieman muuttamalla saada aikaan vieläkin paremmat laatuominaisuudet. Myös tässä kokeessa tutkittiin muuttujien vaikutusta palstautumislujuuteen, geometriseen taivutusjäykkyyteen ja sileyteen. Viimeisen kokeen tarkoituksena oli tutkia samaisen runkoon menevän massan vähentämisen vaikutusta palstautumislujuuteen. Erinäisistä vastoinkäymisistä johtuen, koeajoista saadut tulokset jäivät melko laihoiksi. Kokeista kävi kuitenkin ilmi, että lujuusominaisuudet eivät parantuneet, vaikka jauhatusta jatkettiin. Lujuusominaisuuksien kehittymisen kannalta turha jauhatus pystyttiin siis jättämään pois ja näin säästämään energiaa sekä säästymään pitkälle viedyn jauhatuksen mahdollisesti aiheuttamilta muilta ongelmilta. Vähemmällä jauhatuksella ominaissärmäkuorma saatiin myös pidettyä alle tehtaalla halutun tason. Puuttuvat lujuusominaisuudet täytyy saavuttaa muilla keinoin.

Search Engine Optimization Methods & Search Engine Indexing for CMS Applications

Search engine optimization & marketing is a set of processes widely used on websites to improve search engine rankings which generate quality web traffic and increase ROI. Content is the most important part of any website. CMS web development is now become very essential for most of organizations and online businesses to develop their online system and websites. Every online business using a CMS wants to get users (customers) to make profit and ROI. This thesis comprises a brief study of existing SEO methods, tools and techniques and how they can be implemented to optimize a content base website. In results, the study provides recommendations about how to use SEO methods; tools and techniques to optimize CMS based websites on major search engines. This study compares popular CMS systems like Drupal, WordPress and Joomla SEO features and how implementing SEO can be improved on these CMS systems. Having knowledge of search engine indexing and search engine working is essential for a successful SEO campaign. This work is a complete guideline for web developers or SEO experts who want to optimize a CMS based website on all major search engines.

Simulation and optimization of IGCC technique for power generation and hydrogen production by using lignite Thar coal and cotton stalk

The purpose of this study was to simulate and to optimize integrated gasification for combine cycle (IGCC) for power generation and hydrogen (H2) production by using low grade Thar lignite coal and cotton stalk. Lignite coal is abundant of moisture and ash content, the idea of addition of cotton stalk is to increase the mass of combustible material per mass of feed use for the process, to reduce the consumption of coal and to increase the cotton stalk efficiently for IGCC process. Aspen plus software is used to simulate the process with different mass ratios of coal to cotton stalk and for optimization: process efficiencies, net power generation and H2 production etc. are considered while environmental hazard emissions are optimized to acceptance level. With the addition of cotton stalk in feed, process efficiencies started to decline along with the net power production. But for H2 production, it gave positive result at start but after 40% cotton stalk addition, H2 production also started to decline. It also affects negatively on environmental hazard emissions and mass of emissions/ net power production increases linearly with the addition of cotton stalk in feed mixture. In summation with the addition of cotton stalk, overall affects seemed to negative. But the effect is more negative after 40% cotton stalk addition so it is concluded that to get maximum process efficiencies and high production less amount of cotton stalk addition in feed is preferable and the maximum level of addition is estimated to 40%. Gasification temperature should keep lower around 1140 °C and prefer technique for studied feed in IGCC is fluidized bed (ash in dry form) rather than ash slagging gasifier

Application of simulated annealing in simulation and optimization of drying process of Zea mays malt

Kinetic simulation and drying process optimization of corn malt by Simulated Annealing (SA) for estimation of temperature and time parameters in order to preserve maximum amylase activity in the obtained product are presented here. Germinated corn seeds were dried at 54-76 °C in a convective dryer, with occasional measurement of moisture content and enzymatic activity. The experimental data obtained were submitted to modeling. Simulation and optimization of the drying process were made by using the SA method, a randomized improvement algorithm, analogous to the simulated annealing process. Results showed that seeds were best dried between 3h and 5h. Among the models used in this work, the kinetic model of water diffusion into corn seeds showed the best fitting. Drying temperature and time showed a square influence on the enzymatic activity. Optimization through SA showed the best condition at 54 ºC and between 5.6h and 6.4h of drying. Values of specific activity in the corn malt were found between 5.26±0.06 SKB/mg and 15.69±0,10% of remaining moisture.

Effective diffusivity and convective mass transfer coefficient during the drying of bananas

In this article, a methodology is used for the simultaneous determination of the effective diffusivity and the convective mass transfer coefficient in porous solids, which can be considered as an infinite cylinder during drying. Two models are used for optimization and drying simulation: model 1 (constant volume and diffusivity, with equilibrium boundary condition), and model 2 (constant volume and diffusivity with convective boundary condition). Optimization algorithms based on the inverse method were coupled to the analytical solutions, and these solutions can be adjusted to experimental data of the drying kinetics. An application of optimization methodology was made to describe the drying kinetics of whole bananas, using experimental data available in the literature. The statistical indicators enable to affirm that the solution of diffusion equation with convective boundary condition generates results superior than those with the equilibrium boundary condition.

Economic optimization method to design telescope irrigation of multiples outlets

In this study is presented an economic optimization method to design telescope irrigation laterals (multidiameter) with regular spaced outlets. The proposed analytical hydraulic solution was validated by means of a pipeline composed of three different diameters. The minimum acquisition cost of the telescope pipeline was determined by an ideal arrangement of lengths and respective diameters for each one of the three segments. The mathematical optimization method based on the Lagrange multipliers provides a strategy for finding the maximum or minimum of a function subject to certain constraints. In this case, the objective function describes the acquisition cost of pipes, and the constraints are determined from hydraulic parameters as length of irrigation laterals and total head loss permitted. The developed analytical solution provides the ideal combination of each pipe segment length and respective diameter, resulting in a decreased of the acquisition cost.

Use of interactive performance optimization for identifying the ideal profile of swine finishing producers

The present research aimed to develop a modeling capable of identifying the ideal profile of swine finishing producers using the interactive performance optimization, which began by verifying qualitative the criteria considered most relevant to the decision-making, generating a closed structured diagnosis that covers the socioeconomic aspects about the activity, until the design of a mathematical model able to translate the data obtained in quantitative information. For the verification, it was proposed a practical study for a universe of 120 members of a cooperative in the state of Rio Grande do Sul, Brazil. The results showed that, from the application and the definition of the ideal profile, it was possible to verify that 82 producers are in the group of those who have obtained a "Good" performance, and to 44 the result is in the range between 86% to 90% from the ideal, which means that most have short or medium-term conditions to evolve their status for the considered "Very Good", where only 12.5% of the producers are currently.